Recently, energy issues such as massive blackout due to increase in power consumption
have been emerged, and it is necessary to improve the accuracy of prediction of power …

In order to fully explore the time-series correlation of power load data and improve the
prediction accuracy of power load, this paper proposes a neural network-based deep …

In the process of our daily use of electricity, power load forecasting is very important. Short-
term power load forecasting can effectively manage electric energy. In order to improve the …

With the gradual deepening of power market reform, power generation enterprises'
prediction of their future short-term power generation load is conducive to affecting the load …

Recently, demand forecasting techniques have been actively studied due to interest in
stable power supply with surging power demand, and increase in spread of smart meters …

In view of the inaccurate short‐term power load prediction in the power system, where the
smart grid cannot effectively coordinate the production, transportation, and distribution of …

Due to the influence of many high random factors on the new energy power generation
system, the electric energy output by the generator is extremely unstable, which increases …

The electricity consumption of Chinese users is constantly increasing with the development
of the economy. With the continuous enrichment of residents' lives and the diversification of …

Forecasting domestic and foreign power demand is crucial for planning the operation and
expansion of facilities. Power demand patterns are very complex owing to energy market …

Because of the increasing proportion of power load in sizeable industrial power industries,
this paper proposes a forecasting model based on long short-term memory network LSTM …